Many-objective evolutionary algorithms: A survey
Multiobjective evolutionary algorithms (MOEAs) have been widely used in real-world
applications. However, most MOEAs based on Pareto-dominance handle many-objective …
applications. However, most MOEAs based on Pareto-dominance handle many-objective …
Evolutionary many-objective optimization: A short review
H Ishibuchi, N Tsukamoto… - 2008 IEEE congress on …, 2008 - ieeexplore.ieee.org
Whereas evolutionary multiobjective optimization (EMO) algorithms have successfully been
used in a wide range of real-world application tasks, difficulties in their scalability to many …
used in a wide range of real-world application tasks, difficulties in their scalability to many …
A new dominance relation-based evolutionary algorithm for many-objective optimization
Many-objective optimization has posed a great challenge to the classical Pareto dominance-
based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary …
based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary …
A grid-based evolutionary algorithm for many-objective optimization
Balancing convergence and diversity plays a key role in evolutionary multiobjective
optimization (EMO). Most current EMO algorithms perform well on problems with two or three …
optimization (EMO). Most current EMO algorithms perform well on problems with two or three …
Borg: An auto-adaptive many-objective evolutionary computing framework
This study introduces the Borg multi-objective evolutionary algorithm (MOEA) for many-
objective, multimodal optimization. The Borg MOEA combines-dominance, a measure of …
objective, multimodal optimization. The Borg MOEA combines-dominance, a measure of …
A new decomposition-based NSGA-II for many-objective optimization
Multiobjective evolutionary algorithms (MOEAs) have proven their effectiveness and
efficiency in solving problems with two or three objectives. However, recent studies show …
efficiency in solving problems with two or three objectives. However, recent studies show …
A survey on multi-objective evolutionary algorithms for many-objective problems
Multi-objective evolutionary algorithms (MOEAs) are well-suited for solving several complex
multi-objective problems with two or three objectives. However, as the number of conflicting …
multi-objective problems with two or three objectives. However, as the number of conflicting …
Evolutionary multiobjective optimization: open research areas and some challenges lying ahead
Evolutionary multiobjective optimization has been a research area since the mid-1980s, and
has experienced a very significant activity in the last 20 years. However, and in spite of the …
has experienced a very significant activity in the last 20 years. However, and in spite of the …
On the evolutionary optimization of many conflicting objectives
This study explores the utility of multiobjective evolutionary algorithms (using standard
Pareto ranking and diversity-promoting selection mechanisms) for solving optimization tasks …
Pareto ranking and diversity-promoting selection mechanisms) for solving optimization tasks …
A new evolutionary algorithm for solving many-objective optimization problems
In this paper, we focus on the study of evolutionary algorithms for solving multiobjective
optimization problems with a large number of objectives. First, a comparative study of a …
optimization problems with a large number of objectives. First, a comparative study of a …